Very large, dynamic and complex industrial systems, such as electric power generating plants, petrochemical refining plants, metallurgical and plastic forming processes, etc., have hundreds if not thousands of individual process parameters or variables which interact with one another to produce the eventual plant or process output. For example, when a nuclear power plant is constructed, thousands of sensors and monitoring devices are built in to measure temperatures, flows, voltages, pressures, and a myriad of other parameters. The proper functioning of an industrial process is the result of most (or all) of these individual parameters operating within certain ranges of acceptability.
Heretofore, control of such industrial processes has been effected by establishing a list of the most critical parameters, and identifying the range within which each parameter "should" operate. Typically speaking, these parameters are monitored individually, and if any one (or more) parameter moves outside its normal operating range, the operator is alerted to the out-of-standard parameter. However, all such processes are dynamic--that is, individual parameters within the process may change over time, thereby changing the process to some degree, even though it probably continues to operate normally, as the change in one parameter will typically alter the operation of one or more downstream parameters. Presently, plant/process control is effected by observing whether or not all the monitored parameters are within the expected ranges. If so, the plant/process is presumed to be operating within its designed specifications. However, two major problems arise with this sort of control procedure: (i) if an alarm is sounded, or if a particular parameter moves outside its expected range, an operator has no way of knowing whether or not the alarm is an actual event, or a "false alarm" and (ii) a parameter may be within its expected operating range, but may be trending toward failure, (that is, moving in the direction of soon being outside the normal operating parameters), but an observer presumes the process is operating normally. In the second case, an operator observing the parameter within the normal operating range would perceive no problem with the process when in fact there is a problem which may be too far advanced to easily correct when it finally does move outside the normal operating range. In both cases, a procedure is needed to identify whether or not an alarm signal is in fact a system malfunction, and whether or not various critical parameters are in an acceptable condition or are moving toward failure.
Accordingly, it is an object of the present invention to provide a process whereby numerous parameters in a complex process may be continuously monitored and compared with other process parameters to determine whether or not an alarm signal is an actual failure or a false alarm, and whether or not the critical process parameters are operating in an acceptable condition. Furthermore, the process of the present invention is generally applicable to any system or process regardless of the number of parameters involved and regardless of the manner in which they are expressed.